The invention concerns a device for displaying an internal organ of a patient comprising a computer (2) and a screen (3) connected to the computer in order to display at least one image of the internal organ. According to the invention, the computer is arranged to determine, from at least one medical examination previously carried out on the internal organ, at least one confidence area (10) and/or at least one affected area (11), at least partially encompassing one or more portions (9) of the internal organ where samples have been taken and/or at least partially encompassing one or more areas previously identified as suspect during a medical imaging procedure, and to display, on the screen, the image of the internal organ supplemented with the confidence area and/or the affected area. The invention also concerns a corresponding display method.

An exemplary system, method and computer-accessible medium for characterizing a microstructure of a prostate of a patient can be provided, which can include, for example, generating a magnetic resonance (MR) radiofrequency (RF) pulse(s) by varying (i) a diffusion time, (ii) a diffusion gradient direction, (iii) a diffusion gradient pulse width, or (iv) a diffusion gradient pulse shape, applying the MR RF pulse(s) to the prostate of the patient, receiving a resultant MR signal from the prostate of the patient that can be based on the MR RF pulse(s), determining information regarding a plurality of compartments for the prostate from the resultant MR signal by varying an echo time or a mixing time, and characterizing the microstructure for each of the compartments by applying a microstructural model(s) to each of the compartments.

In some examples, a medical system includes a medical device. The medical device may include a housing configured to be implanted in a target site of a patient, a light emitter configured to emit a signal configured to cause a fluorescent marker to emit a fluoresced signal into the target site, and a light detector that may be configured to detect the fluoresced signal. The medical system may include processing circuitry configured to determine a characteristic of the fluorescent marker based on the emitted signal and the fluoresced signal. The characteristic of the fluorescent marker may be indicative of a presence of a compound in the patient, and the processing circuitry may be configured to track the presence of the compound of the patient based on the characteristic of the fluorescent marker.

A magnetic resonance imaging system can include a basic field magnetic arrangement for generating a main magnetic field and a number of spatially separated imaging regions, the basic field magnetic arrangement including several spatially separated magnet segments, in order to generate segment magnetic fields with a defined segment field direction, at least two of the spatially separated magnet segments being configured in a way that their defined segment field directions are running in an angular fashion to each other so that the segment magnetic fields result in a main magnetic field which has the form of toroid, where the magnetic resonance imaging system is designed to be adapted to MR imaging of dedicated body or organ parts of a patient.

Embodiments facilitate predicting a patient prostate cancer (PCa) DECIPHER risk group. A first set of embodiments relates to training of a machine learning classifier to compute a probability that a patient is a member of a DECIPHER low/intermediate risk group based on radiomic features extracted from bi-parametric magnetic resonance imaging (bpMRI) images. A second set of embodiments relates to classifying a patient as a member of DECIPHER low/intermediate risk group, or DECIPHER high-risk group, based on radiomic features extracted from bpMRI imagery of the patient.

The present disclosure relates to compounds that are useful as near-infrared fluorescence probes, wherein the compounds include i) a pteroyl ligand that binds to a target receptor protein, ii) a dye molecule, and iii) a linker molecule that comprises an amino acid or derivative thereof. The disclosure further describes methods and compositions for incorporating the compounds as used for the targeted imaging of tumors. Conjugation of the amino acid linking groups increase specificity and detection of the compound. Methods and compositions for use thereof in diagnostic imaging are contemplated.

A method of evaluating an image indicating a potential presence of a cancer lesion at a location within a prostate of a patient by transmitting light from an optical probe toward a location, receiving fluorescence spectra by the optical probe from the location, and generating a visual display of a diagnosis classification so as to confirm or contradict the existence of the cancer lesion at the location.

The present invention is directed to a method for calculating tumor detection probability of a biopsy plan and for generating a 3D biopsy plan that maximizes tumor detection probability. A capsule shaped volume is modeled to represent the volume that a biopsy core may sample. An optimization method is used to generate a 3D biopsy plan that maximizes probability of tumor detection for predefined biopsy core numbers and length. Risk of detecting insignificant tumors, also determined by size, and probability of a false negative result is automatically calculated. The present invention also includes a method to determine number and length of biopsy cores required for individual patients determined by the balance of the insignificant/significant probability of detection, prostate size and shape, based upon the previously explained 3D biopsy plan generation method.

Embodiments facilitate stratification of a patient according to prostate cancer (PCa) risk. A first set of embodiments relates to training of a machine learning classifier to compute a probability that a patient has a low-risk of PCa progression based on intratumoral radiomic features and peritumoral radiomic features extracted from multi-parametric magnetic resonance imaging (mpMRI) images. A second set of embodiments relates to classifying a patient as low-risk of PCa progression, or high-risk of PCa progression, based on radiomic features extracted from mpMRI imagery of the patient.

During the delivery of thermal therapy, the measured temperature at each pixel in a cross-sectional temperature slice of a multi-pixel thermal image is compared to a maximum temperature limit. When the measured temperature of a pixel is higher than the maximum temperature limit for a predetermined number of consecutive cross-sectional temperature slices, the pixel is masked if the absolute value of the average difference between the measured temperature at the pixel and the measured temperatures at the pixel's neighbors is greater than a maximum temperature variation. The measured temperature of the masked pixel is ignored in subsequent cross-sectional temperature slices until the delivery of thermal therapy is complete.